Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies

Abstract

Digital footprints, the automatically accumulated by-products of our technology-saturated lives, offer an exciting opportunity for psychiatric research. The commercial sector has already embraced the electronic trails of customers as an enabling tool for guiding consumer behaviour, and analogous efforts are ongoing to monitor and improve the mental health of psychiatric patients. The untargeted collection of digital footprints that may or may not be health orientated comprises a large untapped information resource for epidemiological scale research into psychiatric disorders. Real-time monitoring of mood, sleep and physical and social activity in a substantial portion of the affected population in a naturalistic setting is unprecedented in psychiatry. We propose that digital footprints can provide these measurements from real world setting unobtrusively and in a longitudinal fashion. In this perspective article, we outline the concept of digital footprints and the services and devices that create them, and present examples where digital footprints have been successfully used in research. We then critically discuss the opportunities and fundamental challenges associated digital footprints in psychiatric research, such as collecting data from different sources, analysis, ethical and research design challenges.

Digital phenotyping of suicidal thoughts

“…Finally, a broader issue that extends beyond the scope of this manuscript is the choice of terminology used to address the subtypes of suicidal thinking. Here, we used "digital phenotype" as it most closely matches the work on which this manuscript is based (Onnela, & Rauch, 2016;Torous et al, 2017), although other terminology may also apply here (e.g., "digital footprint"; Bidargaddi et al, 2017).…”

“…However, recent advances in smartphone-based realtime monitoring technology (i.e., ecological momentary assessment [EMA]) (Shiffman, Stone, & Hufford, 2008) have made it possible for the first time to overcome these limitations by allowing individuals to report on suicidal thoughts as they naturally occur in a variety of settings (e.g., over the course of clinical care, in a person's day-to-day life), which has been done in a small handful of studies to date (for review, see Kleiman & Nock, 2018). Indeed, the use of smartphones and related portable devices are providing new opportunities for "digital phenotyping," that is, providing real-time characterization and quantification of human behavior in situ (Bidargaddi et al, 2017;Onnela & Rauch, 2016;Torous, Onnela, & Keshavan, 2017).…”

Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice

“…With research increasingly showing the valuable insights that social media data can yield about mental health states, greater attention to the ethical concerns with using individual data in this way is necessary (Chancellor et al 2019). For instance, data is typically captured from social media platforms without the consent or awareness of users (Bidargaddi et al 2017), which is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness (Guntuku et al 2017). Precautions are needed to ensure that data is not made identifiable in ways that were not originally intended by the user who posted the content as this could place an individual at risk of harm or divulge sensitive health information (Webb et al 2017;Williams et al 2017).…”

Smartphones and Wearables as a Method for Understanding Symptom Mechanisms

“…Digital technologies enable researchers to collect and analyse vast amount of naturalistic data i.e. data collected from individuals in their natural environment (10). This approach, sometimes referred to as 'digital phenotyping' (11), is defined as momentby-moment quantification of the individual-level human phenotype in-situ using data from personal digital devices (12).…”